Senior Machine Learning Engineer for Efficient Time Series Classification
Vor 2 Tagen
We are seeking a highly skilled Senior Machine Learning Engineer to join our team at Siemens AG. The successful candidate will work on developing and implementing efficient time series classification techniques using transfer learning.
Key Responsibilities:
- Design and implement transfer learning techniques for on-site training of time series classification models.
- Develop an algorithm that can adapt to new data autonomously when deployed in the field.
- Identify the most hardware-efficient alternative combining tinyML techniques for implementation on microcontrollers or AI-accelerators.
- Integrate the solution to create real-world impact in an industrial application, showcasing its capabilities and demonstrating on-site model updates.
Requirements:
- Proficient in Python for developing machine learning models and implementing algorithms.
- Experience in C++ for implementing efficient and robust software solutions on embedded systems or AI accelerators.
- Strong background in machine learning, particularly in transfer learning and time series data analysis.
- Familiarity with data preprocessing, feature extraction, and concept drift detection techniques.
- Able to integrate and test software on hardware platforms, ensuring efficient real-time performance.
Compensation and Benefits:
Salary: €80,000 - €110,000 per year, depending on experience.
We offer a comprehensive benefits package, including health insurance, retirement plan, and paid time off.
About Siemens AG:
Siemens AG is a leading global technology company in electrification, automation, and digitalization. We are committed to innovation and sustainability, and we are proud to be an equal-opportunity employer.
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